抗菌剂
抗菌肽
抗生素
抗生素耐药性
生物技术
化学
生化工程
生物
微生物学
工程类
作者
Shuaiqi Ji,Feng An,T.K. Zhang,Miao-Miao Lou,Jiawei Guo,Kexin Liu,Yi Zhu,Jianwen Wu,Rina Wu
标识
DOI:10.1016/j.ejmech.2023.116072
摘要
As antibiotic-resistant bacteria and genes continue to emerge, the identification of effective alternatives to traditional antibiotics has become a pressing issue. Antimicrobial peptides are favored for their safety, low residue, and low resistance properties, and their unique antimicrobial mechanisms show significant potential in combating antibiotic resistance. However, the high production cost and weak activity of antimicrobial peptides limit their application. Moreover, traditional laboratory methods for identifying and designing new antimicrobial peptides are time-consuming and labor-intensive, hindering their development. Currently, novel technologies, such as artificial intelligence (AI) are being employed to develop and design new antimicrobial peptide resources, offering new opportunities for the advancement of antimicrobial peptides. This article summarizes the basic characteristics and antimicrobial mechanisms of antimicrobial peptides, as well as their advantages and limitations, and explores the application of AI in antimicrobial peptides prediction amd design. This highlights the crucial role of AI in enhancing the efficiency of antimicrobial peptide research and provides a reference for antimicrobial drug development.
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